{"id":"W6944351207","doi":"10.18738/t8/ejonhj/fuayce","title":"2018_DIC_UTIG.IMGEO2.FIELD_X.png","year":2024,"lang":"en","type":"dataset","venue":"Texas Digital Library (University of Texas)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Process (computing); Identification (biology); Product (mathematics)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001290664,0.0008837926,0.001130999,0.001246016,0.0001498761,0.0005670089,0.00312208,0.0009078998,0.02319164],"category_scores_gemma":[0.00005579209,0.001067056,0.0008294871,0.001268451,0.0007736982,0.005559894,0.003321608,0.001289115,0.2691941],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001138448,"about_ca_system_score_gemma":0.0004924922,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002619204,"about_ca_topic_score_gemma":0.00005107461,"domain_scores_codex":[0.9964029,0.00008900294,0.0004666291,0.001271369,0.0009434032,0.0008267558],"domain_scores_gemma":[0.9968819,0.000250359,0.000511226,0.001775106,0.00006341459,0.0005179869],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001900866,0.0003152202,0.0009374295,0.0007312778,0.0005388253,0.001156472,0.00002459576,0.000002418376,6.424833e-7,0.000188898,0.9952843,0.0006298691],"study_design_scores_gemma":[0.0005794288,0.0001981313,0.0009679646,0.0005131037,0.0004246162,0.00004534158,0.0001230655,0.0000171606,0.00001274707,0.001320077,0.9947623,0.00103606],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0009955347,0.0008210328,0.000002940366,0.0005015579,0.0006494,0.0004452108,0.9331576,0.0008575738,0.06256917],"genre_scores_gemma":[0.0008836997,0.0002461302,0.0001238816,0.0001823706,0.0002991633,2.220541e-7,0.9363434,0.0001710581,0.06175002],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2460024,"threshold_uncertainty_score":0.999178,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01124730998198251,"score_gpt":0.1933583528852645,"score_spread":0.182111042903282,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}